System and method for defining attributes, decision rules, or both, for remote execution, claim set IV

ABSTRACT

A system of the invention comprises a design module, execution engine, and performance management module. A first computer hosts the design module which enables a user to define attributes, queries, and decision rules transmitted to the execution engine hosted on a second computer remote to the first computer. The second computer can be located at a credit bureau, credit reporting agency, or other data provider. The second computer runs the execution engine to query a data repository with the user-defined attributes and queries, and applies the user-defined decision rules to produce result data transmitted to a third computer hosting the performance management module for monitoring performance of a benefit or offering made with the result data and the corresponding attributes, queries, and decision rules that generated the result data.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent application is a U.S. nonprovisional application that claimspriority under Title 35, United States Code §119(e) to U.S. provisionalapplication No. 60/684,309 filed May 24, 2005 naming Joseph Larry Cash,Edith Dallas Ryan, and Ray F. Bridenbaugh, Jr. as inventors.

BACKGROUND OF THE INVENTION

Some businesses require credit- or marketing-related data from creditbureaus or other third party credit reporting agencies (CRA), and dataproviders, in a transactional manner. These enterprises have individualapplicants or customers for which credit checks are required, and submitrequests for individual credit reports for each customer as needed inthe course of their businesses. An example of this kind of business isautomobile retailing in which sales personnel perform an onlinepre-screen on a potential purchaser to determine the individual'sability to purchase an automobile, the class of automobile they canafford to buy, etc. In other businesses, the request for credit orconsumer data is carried out on a large scale or ‘batch’ basis ratherthan individually. Applications are accumulated, and are then sent inbatches to a credit bureau for processing. In some marketing activitiessuch as sales and credit solicitations, large-scale data queries areperformed by the data provider on behalf of the requesting companiesprior to carrying out such marketing to identify applicants with thedesired characteristics so that the number of applicants produced fromsuch marketing campaign will be worthwhile in relation to the costs ofgenerating those applicants. An example of businesses engaged in largescale solicitations of this nature are credit card companies that sendmass communications or mailings to prospective applicants and thenselect among applicants those to which to offer credit.

Pre-screens, as opposed to obtaining full credit reports, of prospectivecustomers and applicants are performed by these businesses becauseapplicable laws such as the Fair Credit Report Act (FCRA) define certainrequirements for such solicitations, and the manner in which consumercredit data can be used under the FCRA. In any situation lacking anapplication for a benefit sought by permission of the consumerevidencing the consumer's consent, the FCRA prohibits access to anindividual's credit or consumer report. For credit marketing purposes,the FCRA allows the credit file to be used in making business decisionsregarding the consumer, but the FRCA prohibits the business fromaccessing the consumer's credit file directly, without the consumer'sexplicit permission. Thus pre-screening of candidates using a creditbureau or other CRA or data provider is an important step in the processof evaluating the pool of potential applicants that may receiveapplications for a benefit such as a credit card, etc. in a marketingcampaign. Similar consumer protection and privacy laws in countriesother than the United States of America restrict access to consumercredit information.

For large pre-screen activities, businesses generally make requests thatare provided manually to the bureau, CRA, or data provider, and thebureau's own staff is required to program the attributes to define thedata inquiry. This takes both time and resources for the bureau, CRA ordata provider, and results in added cost and delays for the companydesiring the data. In addition, if pre-screened data inquiries are madeof multiple data bureaus, the need for each bureau's staff to programthe attributes results in attributes that are not consistent from onedata provider to another.

Additionally, when these attributes are programmed at the credit bureau,the requesting company encounters difficulty in duplicating the sameattributes for their own use, in their internal system, when making thedetermining decision for respondents to the solicitation campaign. Thisprovides adverse consequences to businesses, because they are requiredunder FCRA to apply the same criteria used in solicitation as they usein accepting applicants. Inability to match the attributes used togenerate a pool of applicants with the attributes used to acceptapplicants under an offer can result in violation of the FCRA and otherlaws.

In addition, by requiring the requesting company to rely on the creditbureau's, CRA's or data provider's internal IT staff, much of thedesired control and capacity to react quickly to changes in businessenvironment is removed from the company making the request. This manualeffort is a significant barrier to the flexibility and speed with whichthese types of data inquiries should be pulled in order to respond tomarket conditions. Consequently, significant resources are presentlywasted because of a lack of automation to permit interaction andcoordination between the involved individuals, the enterprise platforms,and bureau's, CRA's and data provider's computer systems.

Every pre-screen request for large data inquiries and batch processesused for marketing and solicitation involves complex communicationbetween the requesting company and the credit bureau, CRA or dataprovider. There is a request, development, and approval process thatmust be followed for each request for data. In addition, as mentioned,these companies must also use the same attributes used for thepre-screen in the approval process once the solicited applicant applies.Not only is this necessary from a business point of view, it is alsorequired under the FCRA and other consumer regulations. Some companiesmake these large data requests on a weekly basis, requiring complextracking of the different attributes being requested, and the resultsand performance of the data, based upon the attributes used. Thisprocess often results in confusion, and in the end, the abandonment oftracking the inquiry performance against the attributes used to initiatethe data inquiry. Thus, information that could be useful to the companyin conducting its business, or even required by law, is lost. It wouldbe desirable to provide a system that could overcome this problem withprevious technologies.

There is a need in some industries to perform a pre-screen of anindividual on a transactional basis. A good example is in the automobileretailing industry, as previously mentioned. Currently when a customerarrives at the sales floor at an automobile dealership, in many casesthey are asked to fill out a pre-sales application. One aspect of thisapplication is that the customer gives the dealership permission toaccess and pull their credit report. The dealership uses this creditreport as a pre-screening tool to identify the capability of thecustomer to buy, and the line of vehicles their sales person should bediscussing with the customer. This activity is fraught with issues,first and foremost being that there is a high risk that the sales personmay not have permissible purpose to access the customer's credit reportunder the FCRA. This industry, and others like it, requires the abilityto prescreen an individual on a transactional basis, and get the resultsof a pre-screen without pulling the actual FCRA regulated data from thecredit and data bureau which raises FCRA compliance issues.

There is also a need to track attributes and report performance ofsolicitations requiring that the same attributes be used forpre-screening, accepting applications, and evaluating performance ofapplicants accepted for a benefit or product offering of a business.This is difficult for a business to accomplish if the attributes andrules used in the pre-screening, acceptance, and evaluation process haveevolved, as they often do. In addition, the meaning of attributes mayvary among credit bureaus, CRAs and other data providers, furtherobfuscating performance of pre-screen, acceptance, and profitabilityanalyses.

In cases where a decision needs to be made regarding the acceptance ofrisk or the granting of credit, there are the ongoing issues regarding acopy of an individual's credit data being sent from the safety of acredit bureau, CRA, or data provider's database. Recent events in thecredit industry have occurred where a consumer's personal data was sentto fraudsters and other companies for purposes other than FCRA-approveduses. There is therefore a need in the art to provide the capability tobetter protect consumer's data to the benefit of the business, dataprovider, and especially the consumer.

Credit grantors have a need for a system in which they can develop andmanage their own score cards and attributes, yet conduct the dataacquisition and scoring process within the safe confines of a creditbureau's facility. Furthermore, they need a method in which they candevelop and test their attribute and scorecard designs on their owndesktop system. In addition, credit grantors need a system in which theycan have a credit application scored, yet avoid access to the consumer'scredit data which may be subject to severe restrictions or prohibitedunder applicable law.

It would be desirable to provide a system, apparatuses, articles andmethods with the capability to overcome the above-identified problems inthe prior art.

SUMMARY OF THE INVENTION

Certain embodiments of this invention are implemented with computersystems that request, capture, manage, share, and make decisions basedon business enterprise and data information. More specifically, theseembodiments relate to a system, apparatuses, articles and methods forallowing a user to manage, create and apply user-defined data queriesand query attributes, to data searches being performed by data providerssuch as credit bureaus, CRAs, or others, and to receive back theresultant data set or decision. These queries and decision processes mayoccur in a real-time environment or may be run in a batch processingmode, and may include inquiries for multiple applications and applicantsor for single inquiries and decisions regarding an individual person.These inquiries and decisions are performed in a manner to allow theresult set or the decision recommendation to be made, while minimizingtransfer of credit sensitive data from data provider. Some embodimentsof the invention further provide the appropriate tools to track theperformance of the query and attributes.

In one relatively specific embodiment, a method and system is providedto enable a user to define and communicate attributes used forpre-screening data pulled from credit bureaus or other data sources. Thepurpose of the pre-screening may vary, and can be for marketing forcredit granting and solicitation or other purposes. Additionally, thismethod and system can be used to screen and decision credit applicantswithout the risk of passing an individual's credit data to sourcesoutside of the credit bureau, CRA or data provider. It can beimplemented as an execution engine, located at the credit bureau, CRA orother data provider, which searches for data using attributes definedand supplied by a remote user.

In other embodiments, a system and method provides for a software-basedtool at the user's site which supports the design and management of dataselection attributes and the making of pre-screen requests to multipledata providers using the same attributes. These attributes can form thebasis for a large, multi-record pre-screen sort, or the inquiry andscreening of one individual applicant at a time. These developedattributes are passed to the credit bureau, CRA or data providerfacility in an automated fashion, where an execution software engineformats the inquiry into the data provider's format, executes theinquiry against the data provider's database, screens and makesdecisions regarding the data, based on the user's own rules, and thenreformats and delivers the pre-screen results, and/or the decisionrecommendation, back to the user without passing the individualapplicant's unique credit information or other data to the entity makingthe request.

One benefit of certain embodiments of these methods and systems is thatit allows the user to create attributes that are used for dataselection, and place those attributes into production, without the helpof information technology (IT) staff, and such attributes can further beused at a wide variety of data sources. This provides the user thecapability to create an attribute set, and use that same set multipletimes, across multiple data sources (create once, use many).Furthermore, invented embodiments enable the user to attain a muchhigher level of consistency across their data selection sources.Moreover, the user can automate the data inquiry and decision process.The invented embodiments provide the user with the capability to defineand extract bulk data, or single individual data reports, from thecredit bureau or other data source, without requiring the interventionof credit bureau staff with attendant delays and costs. In addition, insome embodiments of the invention, inquiries and attributes composingthose queries, and the performance of the queries, can be tracked forfuture reference and repeat performance.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Having thus described the invention in general terms, reference will nowbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 is a block diagram of a system and apparatuses of the inventionshowing the design module, execution engine and performance managementmodule in accordance with the invention;

FIGS. 2A-2C are various flow diagrams indicating how specification filesand decision files can be used to generate result data for a marketingcampaign in accordance with the invention; and

FIGS. 3A-3O are various user interface diagrams indicating variousfeatures of the claimed invention.

DETAILED DESCRIPTION OF THE INVENTION

The present inventions now will be described more fully hereinafter withreference to the accompanying drawings, in which some, but not allembodiments of the inventions are shown. Indeed, these inventions may beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein; rather, these embodiments areprovided so that this disclosure will satisfy applicable legalrequirements. Like numbers refer to like elements throughout.

GENERAL DESCRIPTION

The disclosed invention, in its various embodiments, solves the needsand problems of the prior art addressed above. The invention provides asystem, apparatuses, articles and methods for defining, communicating,and configuring data queries that can be processed by a computer togenerate pre-screens or credit- or risk-based decisions, which cantranscend organizations, data bureaus, CRAs, or other data providers,and their specific internal operations.

Various embodiments of the invention provide a system, apparatuses,articles and methods that can allow the credit bureau's, CRA's, or dataprovider's user to define, configure, and communicate a computerprocessable data query, for batch or individual pre-screen purposes, toa credit bureau, CRA, or other data providers, and to receive back theresult data set in response. Such embodiments also provide thecapability to maintain a complete record and audit trail of theattributes and rules used to generate the result data set. Such acombination of a definition system, coupled with the audit trail andperformance data, can enable continuous process and businessimprovement.

Additional embodiments of the invention provide for a system,apparatuses, articles and methods that allow the credit bureau's, CRA's,or data provider's user to define, configure, and communicate acomputer-process-able data query, for credit and risk decision purposes,to a credit bureau, CRA, or other data providers, and to receive backthe recommended decision, along with appropriate reason codes, based onthe credit data in the bureau, without actually sending the bureau dataoutside of the credit bureau itself. These embodiments may provide thecapability to maintain a complete record and audit trail of theattributes and rules used to generate the resultant decisionrecommendation. Such a combination of a definition system, coupled withthe audit trail and performance data, can enable continuous process andbusiness improvement, as well as improved processes for consumer datasecurity.

Additional embodiments of the invention can track the performance andsuccess of an attribute definition, so that as future attributedefinitions, decisions, queries, and demographic decisions are made, thebusiness can evolve their selections and make continual improvements,and better business decisions.

Also, various embodiments of the invention are open and extensible,providing the ability for future revisions, added capabilities, orenhancements being made.

System Overview

To meet the goals, the system 100 of this invention has multiplecomponents which are described herein and shown in FIG. 1. Fordescription purposes, the three components are:

-   -   (1) the design module 200, which is used at the client's site        500;    -   (2) the execution engine 300, which runs at the credit bureau,        CRA, or data provider's site 600; and    -   (3) performance management tool 400, which is used at the        client's site 500.        The design module 200 is used by the end-user, such as a credit        risk manager or marketing analyst of the client 500, to design        the specifications for data attribute calculation, the report        display format, and the optional rules and score card for credit        risk decision rules. These rules for score cards and credit risk        decisions are used in response to inquiries 220 generated within        the client or received from an external entity 225 through the        transaction manager 230. Once the specifications have been        designed, a process within the design module is executed, which        gathers the design specifications and writes them to several        files 205, 210. The computer hosting the design module 200        transfers the files 205, 210 to the data provider, possibly via        communication network 700 such as the Internet or a private        network, for execution in the data pre-screen or credit risk        decision process.        Within the data provider 600, the execution engine 300 operates.        This engine executes queries with the user-defined attributes to        identify data of interest to the client, and applies the        decision rules 210 to generate pre-screen or decision result        data 335 which is provided back to the remote client.        More specifically, within the data provider 600, the following        steps occur:

-   A. The data acquisition tool 310, in response to an inquiry from the    transaction manager 230 transmitted via a communication network 700,    queries the repository 305, and retrieves the credit report data    307.

-   B. The data records are then sent to, and processed through the data    analysis module 315 to create the specification files 205 and the    human-readable report display (the later being optional), as    previously defined by the client using the design module 200.

-   C. If a risk decision is required, the client's decision rules 210    generated using the design module 200 are applied to the data by    decision module 325 of the execution engine 300, and a recommended    decision, optionally including codes defining the reason(s) for the    decision(s), are formed and output as result data 335.

-   D. For pre-screen inquires, the data records are filtered by the    criteria filter module 330 according to the client's own criteria in    files 205 and 210 in order to generate the prescreen list 335.

-   E. Depending upon the nature of the inquiry 220, which as mentioned    can originate within the client or externally from another entity    225, the result data 335 such as a risk decision and reason code, or    the resultant pre-screen list, is returned to the user's site 500    and into the performance management tool 400 for the logging of    audit trails and performance metrics and the return to the    requesting user through the transaction manager 230.

One significant benefit of this system is that it requires no customprogramming at the data provider 600. This helps to reduce the timerequired for the client to generate results 335, and also helps toensure accuracy of the data because the client has defined theattributes used in generating the results and thus has accurateknowledge of what the attributes signify. In addition, a further benefitis that the credit data used to generate the pre-screen results and therisk decisions, does not need to leave the credit bureau's premises.This helps to ensure the privacy of the consumer's data, which clearlybenefits the consumer. In addition, the data provider is required by lawto maintain the privacy of the consumer's data, so use of the datawithout exposing that data outside of the data provider benefits thedata provider. The client is benefited because the results 335 can begenerated so as to include data controlled by the FCRA and otherapplicable law, and thus, compliance issues such as data privacy andpermissible purposes are simplified for the client.

Design Module 200

As previously mentioned, the design module 200 is a software tool thatruns at the user's location 500. The design module 200 has the followingbasic specifications:

-   Code Table Specification—The user has the ability to define, edit,    copy and delete codes and their text translation for the purpose of    then grouping together like codes for use in data attribute    definitions and/or display on the human-readable report.-   Operand List Specification—The user has the ability to define, edit,    copy and delete lists of operands identified by codes for use in the    definition of data attributes.-   Data Attribute Specification—The user has the ability to define    attributes and unique data attribute calculation logic based on the    data source/version, and can edit, copy, and delete specifications    as needed.-   User Defined Display (UDD) Specification—The user has the ability to    define the format the data that is to be presented for    human-readable purposes. The user can define a summary, page header,    page footer, and segment(s) detail displays. The drop and drag user    interface allows for simulation of “painting” the requirements for    display on a palette. The user defined display capabilities allow    for data masking of fields such as dates, telephone numbers, and    dollar amounts so formats can be specific to user's desires. Unique    display specifications can be defined to satisfy different user    group needs such as unique report displays for different    departments, product lines, promotions, and data providers.-   Result Record Structure—The user can define the data structure(s)    layout expected by their application or decision system.-   Decision Rule Sets—The user can create decision rules 210 based on    data attribute results or other reference-able data. Individual    rules can be combined to form rule groups and then further grouped    to create decision rule strategies. These rules can be created,    edited, and deleted.-   Element Definitions—Element definitions are built-in for most common    data elements, such as data formats, functions, and data provider    codes.-   Custom Data Definitions—The user has the ability to create data    tables to describe customer specific data to be used in the data    attribute calculation process.-   Business Unit Management—The user has the ability to create unique    code tables, operand lists, data attribute and user-defined display    specifications, and decision rules for each organizational segment    defined (i.e. business unit, division, product group).-   Copy—The user has the ability to copy previously defined data    attributes into any other business unit or data provider defined by    the user in the design module, and then alter or modify those    attributes as he or she desires.-   Cross-Referencing—The user has the ability to cross-reference other    data attribute definitions and decision rules into a new definition    or decision rule group.-   Reference Checks—Reference checks are available to help users    understand the relationships between various data attributes and    decision rules. These checks assist in preventing a user from    inadvertently removing an attribute or decision rule that is still    being referenced elsewhere.-   Display Data Elements—The design module provides the capability to    display all data elements retrieved from any or all data providers.-   Flat File Export—The design module provides the capability, on the    command of the user, to generate a flat file from the defined    attributes or decision rules, for the purpose of uploading to the    execution engine running on a mainframe or other platform. These    flat files are named by the design module with a unique system    identifier which will identify the date of creation, and the    definitions.-   Audit Trail for Flat File—The flat file record used to communicate    attributes and decision rules from the design module 200 to the    execution engine 300 are maintained for audit and performance    management purposes. This file contains the date and time of the    attribute/decision rule creation, the author of the    attributes/decision rules, as well as all attribute/decision rule    definitions.-   Inventory—The system maintains an inventory of data attributes and    decision rules which allows the user to quickly locate and put to    use previously defined specifications.-   Multi-platform Support—The design module 200 can be configured to    run on a desktop operating system of the user's choice. For example,    the design module can be run on a Microsoft Windows-based personal    computer, or other platform.-   Scheduling—The design module 200 can be used to implement changes    scheduled to occur at future dates and times.-   User Interface—The user can be presented with a Microsoft Windows    style user interface which allows improved usability and easy    creation of data attribute specifications 205 and decision rules    210.-   Data Management—Full backup and restores of all specifications 205,    210, 405 are supported in the application and can be used to manage    change control.-   Concurrent User Access Controls—Multiple users have the ability to    perform functions in the system at the same time. However, controls    are in place to prevent users from updating the same record. Once a    specification has been selected by one user, it is locked and other    users selecting the same record have a view-only version.-   User Security & Permissions—Only users defined to the system have    access. User permissions can be maintained in the application to    restrict create, edit, copy, and delete functions. Users can be    restricted to specific business unit specifications and may have    different permissions within different business units.-   Security Audit logs—Audit logs are maintained of failed logon    attempts.

Execution Engine 300

The execution engine 300 operates at the credit bureau, CRA, or otherdata provider's location 600. It is installed to operate in a nativefashion on the data provider's mainframe or other platform of choice forprocessing the data inquiries.

The execution engine 300 has the following basic features:

-   Flat File Import—The execution engine 300 has the ability to import    a flat file containing attribute definitions from the design module    200, and then interpret the data in the flat file to provide new    attributes for filtering data.-   Data Analysis—The execution engine 300 has the ability to take data    and summarize it, based on the defined attributes (205 file), for    further screening. This summarized file is then stored for further    filtering.-   Screening—The execution engine 300 analyzes the data contained in    the attribute file against the attribute definitions imported from    the design module 200, filtering for those records that meet the    attribute definition. Those records that satisfy the definitions are    exported into a data file 335 for delivery back to the client. The    exported file is stamped with the audit trail number which    identifies the attribute definition as defined by the design module    200 (other related files are similarly stamped with the audit trail    number in order to correlate such files so that, for example,    attributes and decision rules used to generate a pre-screen list can    be matched to attributes and decision rules used to accept    applicants or gauge performance of the attribute and decision rule    sets in obtaining desired customers).-   Testing—The execution engine 300 provides the user with debugging    and testing capabilities through which the user can test and    validate their data attributes 205 and decision rules 210.-   Test Environment—The user can create a test environment for the    purpose of validating new data attributes 205. The user can transfer    credit reports to this test environment, as needed, for data    validation.-   Test Facility—The execution engine 300 provides a test facility    which will allow for testing of data attributes 205 using retained    data.-   Audits of Characteristic Results—The execution engine 300 maintains    and makes available the full data attribute results with detailed    audits for the purpose of testing.-   Audits Online—The user is capable of running online audits for error    correction and troubleshooting.-   Audit Reports—Detailed audits are used to validate the results of    data attributes 205 and decision rules 210. During the quality    assurance (QA) process, these audits will be available for error    resolution.-   Format Conversion—The execution engine 300 has the capability to    convert raw bureau data 307, extracted from the data provider's data    base, into a format used by the performance management module 400    and the design module 200. This formatted data is then used by the    execution engine 300 for filtering the data based on the defined    attributes.    For support in generating the logic for attributes 205 and decision    rules 210, the execution engine 300 also supports the following    functions:-   Mathematical Functions—absolute value, exponentiation, natural    logarithm, rounding (including round-up and round-down), square, and    square root. These are functions that receive a numeric input and    produce the result by applying the named mathematical function.-   Action Functions—Clear and store are action functions that change    the data contents of a field. The GOTO function is an action that    forces an unconditional change in the sequential flow of the scoring    process.-   Comparison Function—The IF function compares two values (a field    against another field or against a literal) and allows the user to    assign a reason codes (optional), point score or status codes and    choose a connector based on the user's decision strategy.-   Score Functions—Coefficient (characteristics-coefficient product)    and expected value are functions used to alter the score or ordering    of reasons assigned during scoring.-   Calculation function—Performs a linear arithmetic computation and    produces a numeric result.-   Matrix function—This function produces a two dimensional table that    allows a user to examine two variables and set a value in the    resulting variable.

Performance Management Module 400

The performance management module 400 is designed to provide futuretracking of specific attribute performance in relation to the success ofthe data pulled from the bureau.

The performance management component has the following basic features:

-   Audit Data Import—The performance management module 400 allows the    user to seamlessly import the audit data 205, 210 from the design    module 200. This data file contains the audit trail ID, the    attributes defined, the author of the attributes, and the associated    date and time stamps.-   Performance Data Import—The performance management module 400 allows    the user to import results data 335 in a flat file for each    attribute audit file being tracked. This file contains the number of    responses generated from the attribute file, the financial revenue    generated from the attribute file, the campaign costs associated    with any specific attribute or mailing, the date of the record    updates, the default rate of the credit loans associated with the    attribute file, and other data deemed necessary for the performance    tracking of the campaigns.-   Performance Reporting—The performance management module 400 allows    the user to view on a screen or in printed reports the performance    summary of each attribute. This summary includes the number of    solicitations created by the attribute selection, the time    associated with the campaign, the cost of the campaign, the gross    revenue generated from the campaign, and the net revenue generated    from the campaign. The user is also able to use the module 400 to    compare the performance of one attribute with the performance of    other attributes as defined and selected by the user. The user can    ‘drill-down’ (in other words, obtain further details regarding)    specific attribute campaigns to view the specific summary. The user    can further drill down below the summary level to view attributes    and the data source provider.-   Dashboard—The performance management module 400 has the capability    of showing a management dashboard which summarizes performance data    from the desired date range or campaign selection. This tool    provides a summary view of performance and campaign characteristics.    When any dashboard item is selected by clicking on it, this    selection allows the user to drill down into the data, business    objects, and attributes which make up and are responsible for the    summary report. The user is able to continue clicking on layers of    information until the user drills down through the various layers of    data to the data elements or selection criteria which satisfies the    user's questions or inquiry.-   Attribute Recall—The user is able to use the module 400 to select a    past attribute or business object from a performance report or    summary, and by clicking on it, open the attribute definition file    in the design module 200.

EXEMPLARY METHODS AND SYSTEM OPERATION

FIGS. 2A-I and 2A-II are flow diagrams of a method in accordance with anembodiment of the invention. The method is applied to the system 100 andis thus useful for describing the operation of such system in thecontext of performing a pre-screen for a marketing campaign. In Step (1)of FIG. 2A-I the user (e.g., risk manager) operates the design module200 to define the attributes and decision rules 205, 210 to be used forthe pre-screen selection to generate result data 335. In Step (2) theuser operates the design module 200 to export the defined attribute 205and decision rules 210 to the credit bureau, CRA, or other data provider600 to be used to generate result data 335. In Step (3) the executionengine 300 acquires the target data 307 with data acquisition module310. The execution engine 300 analyzes the data 307 and scores the datarecords based on the specification rules 205 and decision rules 210.More specifically, the execution engine 300 retrieves the data 307 usingthe data acquisition module 310. The data acquisition module 310 passesthe target data 307 to the data analysis module 315 that applies thespecification files 205 with defined attributes to generate the data forfurther processing. The decision module 325 receives this data andapplies the decision rules 210 in order to generate output datareflecting pre-screens or decision(s). The criteria filter 330 appliespredefined criteria to the data to generate result data 335 which can bea pre-screen list or recommended decision(s). In Step (5) of FIG. 2A-IIthe execution engine 300 receives the data records 335 from theexecution engine 300 electronically via network communication media suchas the Internet, by tape transported via mail, or other means. The datarecords 335 can thus be delivered to the client's fulfillment center. InStep (6) the same attributes of specification files 205 and decisionrules 210 used for the initial pre-screen are loaded into an executionengine 800 at the client's location. In Step (7) the attribute data,dates, pre-screen result data 335, and any other desired performancemetrics, are loaded into the database of the performance managementmodule 400. The result data 307 is used to generate marketingsolicitations for a campaign. In Step (8) responses from the campaignare received and input into the credit decision system 800 of client500. In Step (9) credit applicants are sent to the credit decisionsystem 800 for credit decision using the same rules 210 applied for thepre-screen. In step (10) the application response data, acceptance data,and other performance metrics are loaded in the performance managementdatabase 400. The performance management module 400 has the datanecessary to be useful for managing the campaign or analyzing thecampaign results.

FIGS. 2B-I and 2B-II are flow diagrams of a method in accordance withanother flow diagram of the invention. In Step (1) the user (e.g., riskmanager) creates the attributes 205 and decision rules 210 for use inthe pre-screening of prospective or actual applicants on a transactionbasis. In Step (2) the attributes 205 and decision rules 210 areexported to the execution engine 300 of the data provider 600. In Step(3) the attribute and decision rule files 205, 210, dates, and possiblyother metrics, are loaded into the execution engine 300 of the dataprovider 600. In Step (4) pre-screen inquiries 225 are received by theclient 500 on an individual or transaction basis, and are processed intothe credit decision system of the client 500 via the inquiry andtransaction manager 230. In Step (5) of FIG. 2B-II the execution engine300 acquires the data 307 and analyzes and scores the records 307 basedon the attributes 205 and rules 210. More specifically, the executionengine's data acquisition module 310 acquires the target data 307, andthe data analysis module 315 applies the user-defined attributes andlogic in the specification files 205 to identify data of interest to theclient. The execution engine 300 applies the user-defined decision rules210 to determine result data, and applies the criteria filter 330indicating results to be reported to the user, in order to generate theresult data 335. In Step (6) the result data 335 is returned to theclient's transaction manager 230. In Step (7) the pre-screen result data335 is transmitted to the entity from which the inquiry originated(e.g., an automobile retailer). In Step (8) performance management data335 is received from the data provider 600 and/or the inquirer 225 inresponse to the prospective customer's performance (e.g., applicationfor credit, acceptance for credit, customer payment performance on thecredit, etc.).

FIGS. 2C-I and 2C-II are flow diagrams of a method in accordance withyet another embodiment of the invention. The method of FIG. 2C-I isuseful for contexts in which decisions to extend credit are to be madeat the data provider 300 under user-defined rules 205 and 210 for abatch of requests for a benefit such as extension of credit. In Step (1)the user (e.g., risk manager) creates the attributes and decision rules205, 210 to be used to generate result data 335. In Step (2) theattribute and decision rules 205, 210 are exported to the executionengine 300 of the credit bureau, CRA, or data provider 300. In Step (3),the attribute data 205, decision data 210, any date stamps indicatingwhen the data 205 and 210 was created, score card data, and otherinitial metrics, are loaded into the database of performance managementmodule 400. In Step (4) outside inquiries 225 such as creditapplications are received and processed into the credit decision systemof the client 500. The credit applications can be received and processedby the inquiry and transaction manager 230. In Step (5) the executionengine 300 at the data provider 600 receives the request, acquires thedata responsive to the credit application based on the definedattributes and logic of specification files 205, and scores the creditapplication based on the user-defined attributes 205 and decision rules210. More specifically, based on information from the credit application(such as the applicant's name, address, etc.), the execution engine'sdata acquisition module 310 retrieves relevant data 307 from the datarepository 305, and provides the same to the data analysis module 315which applies attributes and logic 205 to the data to generate a set ofdata upon which the decision module 325 applies the user-defineddecision rules 210 to produce a credit score or the like. The criteriafilter 330 extracts selected data relevant to the user's inquiry togenerate result data 335. In Step (6) the risk decision is returned tothe client's inquiry and transaction manager 230. In Step (7) thetransaction manager 230 transmits the pre-screen result data 335 to therequestor 225. In Step (8) the result data 335 is sent to theperformance management module 400 to manage the business related to theinquiry 220. In Step (9) the performance management module 400 is usedto manage the credit business based on the attribute and logic data,response data, result data, acceptance data, payment performance datareflecting the debtor's performance, etc.

User Interfaces

FIG. 3A is a user interface 240 generated by design module 200 executedby the computer 201 in order to permit a user to maintain a set of codes241 to be used to define one or more attributes of the specificationfile 205 and/or provide the equivalent text description on the reportdisplay to make the information more clear to a human reader. The usercan operate mouse-controlled cursor 243 to select a data provider (e.g.,‘Equifax’), a version (e.g., ‘5.0’) of the data provider's codes, thespecific code set (e.g., ‘Industry Codes’) the user wishes to select. Adescription associated with that code set, as well as how those codesmap to the data format (‘MCF fields’) used by the design module 200 isreturned. In the example of FIG. 3A, the user selects ‘Industry Codes’and the corresponding codes 241 are shown in the list 244. The codes 241are computer-usable characters that enable the data provider 600 tocommunicate corresponding data. Corresponding descriptions 245 can beadded which describe the codes 241 in text in a way that is moreunderstandable to a human user. The user has the ability to add codes241 to the list 244 by using the cursor 243 and keyboard of computer 201to enter the letters for the code 241 and corresponding description 245,into respective fields 246 and operating the ‘Add’ control 247. The usercan also delete a code 241 and its description 245 from the list 244 byusing the cursor 243 to select the code in the list 244, and operatingthe ‘Remove’ button 247. A set of codes 241 for an attribute or reportdisplay can thus be defined. In addition, using controls 248, the usercan select the ‘New’ button to create an entirely new list of codes 241.The user can also operate the ‘Copy’ button to copy a set of codes 244as a starting point for creating a new set of codes. Furthermore, theuser can operate the ‘Edit’ button to modify an existing list 244 ofcodes 241. In addition, the user can operate the ‘Delete’ button inorder to delete a list 244 of codes 241. As with the other userinterfaces described herein, operating the ‘Close’ button at the bottomof the user interface 240 causes the design module 300 to close theinterface window.

FIG. 3B is a user interface 250 generated by the design module 200executed by computer 201 in order to permit a user to specify from acode list 244 the codes 241 to be used by an attribute assigned to aspecification file 205. The user interface 250 includes a list 244 ofcodes 241 representing portions of data content within a data provider'srepository 305. The codes, and corresponding descriptions 245 enable ahuman user to understand the meaning assigned to the code 241, aspreviously explained. Controls 251 are software buttons that enable theuser to select and de-select codes 241 from the list 244 for inclusionin or deletion from an operand list 252 that will be used in attributespecification. By using mouse-controlled cursor 243, a user can selectone of the codes 241 and click the ‘>’ control 251, a software button,to add the code 241 to the list 252 of operands to be used by anattribute for a specification file 205. Selecting the ‘>>’ control 251adds all of the codes 241 from the list 244 to the list 252 of operands.Selecting one of the codes 241 in the existing operand list 252 andoperating the ‘<’ control 251 results in deletion of the code from theoperand list 252 and adding of such code to list 244. Selecting the ‘<<’control 251 with the cursor 243 causes all codes 241 from the existingoperand list 252 to be deleted from such list and adds such codes tolist 244. Using fields 253, the user can operate the design module 200to identify the operand list 252 of codes 241 for an attribute by thename of the data provider (e.g. ‘Equifax’), the version of the operandcodes for that data provider (e.g., ‘5.0’), the list name (e.g.,‘BANKCARD’) assigned to the list 252, and a description of the operandlist 252 for easier comprehension of the meaning or purpose of theoperand list to the human user. Controls 254 provide variouscapabilities. The ‘New’ control 254 enables the user to create a newlist 252 of operand codes 241. The ‘Copy’ control 254 enables the userto copy an existing list of operands 252 for a new list 252 to enablethe user to re-use a previously defined set of operands, or to enablethe user to save time by modifying an existing list of attributes inorder to define a new list 252, for example. The ‘Edit’ control 254enables the user to modify an existing list 252 of codes 241 for anattribute.

FIG. 3C is a user interface 255 that enables a user to define anattribute or variable 256 with the design module 200 running on computer201. The user interface 255 includes fields 257 to enable the user ofdesign module 200 to define the attribute name (i.e., computer-usablecode name) and a textual description of the attribute to enable a humanuser to understand the meaning or purpose of the attribute. Furthermore,the user interface 255 provides fields 258 which enable the user tospecify variable name, data provider, version, and segment/output fileof the data provider to which the attribute 256 relates. Also includedin the user interface 255 is an object or function name 265 (e.g.,‘OBNT0003’) which defines the logical operation on the data that is tobe carried out, for example, by the execution engine 300 at the dataprovider 600, in order to derive the value to be associated with theattribute 256. For example, the object or function can be an accumulatefunction that adds values associated with data elements, or an averagingfunction that averages values associated with data elements, or afunction that adds, subtracts, multiplies or divides values associatedwith data elements, or other mathematical or logical operation. Theclient and site fields 258 identify the client name and client site forwhich the variable is relevant, in addition to the name of the variable,the data provider (e.g., ‘Equifax’) for which it is relevant, theversion of the data provider's specification (e.g., ‘version 5.0’) forwhich it is relevant, and the segment/output specification file 205 withwhich the attribute is associated. Controls 259 enable the user to savethe new attribute via the ‘Save’ button, or to cancel the attributeusing the ‘Cancel’ button. The variables specification interface 255provides various tab selections 249 which enable the user to view‘Specifications’, ‘Sets’, and ‘Comment’ screens. The user interface 250of FIG. 3B results from selecting “Variable Specification” from the mainmenu.

In FIG. 3C the user interface 255 produced by design module 200 runningon computer 201 provides the user with the ability to identify anyparameters required to calculate the attribute logic. The view of theuser interface 255 of FIG. 3C is that resulting on opening a variablespecification or selecting the ‘Specification’ tab. It enables the userto select that data associated with the attribute 256 that the userrequires in the result data 335. The controls 259 enable the user toperform various functions. The ‘New’ control 259 can be activated by theuser with a mouse, for example, to create a blank template with fieldsto receive text to define a new variable. The ‘Copy’ control 259 enablesthe user to copy and existing variable for the creation of a new one.The ‘Extend Variable’ control 259 enables the user to re-purpose anattribute for use in creating other functions. The ‘Delete’ control 259enables the user to delete a variable specification. The ‘History’control 259 enables the user to review the history of creation andrevisions of a variable. The ‘Save’ control 259 enables the user to savethe variable specification and any changes made thereto. The ‘Cancel’control 259 enables the user to cancel any changes made to the fields ofthe template for the variable specification.

In FIG. 3D a user interface 255 is shown after selection of the ‘Sets’tab 249 using the design module 200 of the computer 201. Selection ofthe ‘Sets’ tab 249 and selection of the ‘Parameters’ tab 262 results ingeneration of a list of parameters 264 associated with the function 265(which in this example is ‘Accumulator (Processor)—OBNT0003’). Thelisted parameters 264 are identified by name (e.g., Accumulate Field 1,Accumulate Field 2, etc.), parameter type (e.g., Numeric Field), datatype (e.g., ‘N’ meaning numeric), ‘Option’ field indicating whether theparameter is optional or required, and value field identifying the valueto be associated with the parameter (e.g., ‘BALANCE’ is the value to beassociated with the result of carrying out the function of accumulatingdata values in fields, 1, 2, etc.) which are specified for the variable.Operation of the ‘Reset’ control 267 enables the user to reset aselected parameter 264 to blank fields. Using the ‘Add’, ‘Remove’ or‘Reorder’ tabs 261, the user can add, remove or reorder sets ofparameters/rules. In addition, using the ‘▴’ or ‘▾’ arrows, the user canscroll up or down to view the parameter/rule sets of specificationsdefined to calculate the attribute result.

FIG. 3E is a view of a user interface 255 resulting from the user'sselection of the ‘Rules’ tab 262 with a mouse or other input device. Italso enables the user to specify the data associated with the attribute256 that the user does not want to receive in order to avoid needlesscomplexity in the result data 335 as well as avoiding receipt of datathat may be prohibited or use-restricted under applicable law such asthe FCRA. In this exemplary view, rule 269 is identified in the firstand only line of list 270 which includes all rules related to thevariable 258. The rule 269 includes data entries identifying the linenumber of the rule 269 in the list 270, the source of the rule 269 whichindicates its format (e.g., ‘Common Format’), a field identifying thecode set with which the rule 269 is associated (e.g., ‘INDUSTRY CODE’),a comparison field which indicates the logical operation related to thefield code (e.g., ‘=’ signifies a comparison of equality between thevariable and the data sought, in this example, equality), the‘List/Literal’ field (identified as ‘BANKCARD’ in FIG. 3E) signifiesthat the literal or operand list 252 name sought in the data is the oneassociated with the name ‘BANKCARD’. The connector field identifies thelogical operation to be performed with the rule following in the list270. In the case of FIG. 3E there is no rule specified following the‘connector’ field so that logical operation ‘AND’ is assigned to thefield by default.

FIG. 3F is a view of a user interface 275 generated by design module 200executed by computer 201. The user interface 275 is used to define files205, to be exported from the client 500 to a data provider 600 forexecution on its execution engine 300. In FIG. 3F the ‘ExportData’ tab276 is shown and it identifies a list of data providers 600 to which thefiles can be exported. By selecting one or more of the data providers inlist 277 and pressing the ‘>’ button 278, a file can be selected andadded to the list 279 of files for export. Conversely, by selecting afile from the list 278 (no files are present in list 278 in the exampleof FIG. 3F), and operating the ‘<’ button 278, a file can be deletedfrom the list 278 so that it is not exported to a data provider 600, butis added to the list 277. Control 280 will be explained with referenceto FIG. 3G. Control 281 can be used to generate files 281 into a formatsuitable for export. Control 282 enables the user to specify the samefiles as the previous export operation for export in the current exportoperation.

FIG. 3G is a view of the user interface 275 generated by design module200 on computer 201. The user interface 275 shows the presentationresulting from the user's selection of the ‘Variables’ tab 276. The userinterface 275 shows a list 283 of variable names in association with‘Audit’ and ‘Export’ checkbox options. The Audit option enables the userto select from the list 283 of variables 256 those for which the userdesires to record all data and actions executed to calculate theattribute result. The Audit option is useful for testing use of thedesign module 200 and/or export module 300 by providing the data used togenerate a variable to ensure that the design module and export moduleare working as the user intended. It may also be helpful to a user to beable to determine the meaning attached to the data by the data providerso that data from different providers can be used despite differentsemantic meanings attached to the data. The Export option enables theuser to select from the list 283 the variables to be exported to thedata provider 600 for computation by the export module 300 at the dataprovider's location. Controls 284 provide various conveniences to theuser, including a ‘Select All’ control to enable the user to select allvariables 256 in the list 283 for audit, a ‘Select None’ control toenable the user to select none of the variables 256 in the list 283 foraudit, and a ‘Same As Last Export’ control to enable the user to repeatthe variables 256 selected for audit from the list 283. Similarly,export controls 285 provide the user with the ability to ‘Select All’variables 256 in the list 283 for export to an export module 300 of adata provider 600 for computation, a ‘Select None’ control operable bythe user to de-select variables 256 for export, and a ‘Same as LastExport’ control to enable the user to repeat the selection of variables256 used in the previous export operation.

FIG. 3H is a view of ‘Generate Export Files’ user interface 2070generated by the design module 200 of the computer 201. The userinterface 2070 enables the user to specify those files 205 that are tobe exported to the execution engine 300. The user interface 2070 is thatresulting by selection of the ‘Export Files’ tab 2072. The user canactivate check box 2072 to indicate that a ‘Code Table’ or code file(s)2052 is to be exported. By entering the filename (‘CT.dat’), in thefield 2074, the user can specify the code file(s) 2052 to be exported.By activating the check box 2073, the user can indicate thatspecifications 205 are to be exported to the execution engine 300. Byentering the filename (‘VC.dat’) of variable file(s) into field 2075,the user specifies the variable file to be exported. By entering thefilename (‘PS.dat’) into the field 2076, the user specifies theparameter file to be exported. By entering the file name (‘OP.dat’) intothe field 2077, the user specifies an output file to be exported to theexecution engine 300. Finally, by entering the filename (‘UDD.dat’) intothe field 2078, the user enters the display format 2004 the user desiresfor the result data 335. Using the Directory field 2079, the user canspecify the path and filename for the directory to hold thespecification files for export. Export can be implemented by designmodule 200 or some other component of the client's system, eitherautomatically (e.g., via server application using HTTP protocol) or withmanual intervention (e.g., email). The user interface 2070 of FIG. 3Halso includes a ‘recount variables’ control 2080 that can be used by theuser to count the variables in the export file as a check to ensure thatthe correct number of variables are in the export file as a check forany editing of variables carried out by the user. Finally, the ‘GenerateFiles’ control 2082 actually creates the file(s) to be stored at thedirectory location specified in field 2079. The computer 201 can beconfigured to automatically export the files from the directory locationspecified in field 2079, optionally with the user's involvement (e.g.,emailing the directory to the data provider 600 for import to theexecution engine 300). Although not shown, the decision rules can beoutput to the directory for export to the execution engine 300 using aninterface similar to the user interface 2070 of FIG. 3H.

The ‘Output File Mapping’ user interface 290 of FIG. 3I is generated bythe design module 200 executed with the computer 201. The user interface290 is used for creating the record structure of the result file 335that will contain the attribute results generated by the export module300. The user interface 290 includes fields 291 for identifying theclient and site to which the file mapping is relevant, as well as aselectable field to enable the user to select a file name from among alist of possible files (in FIG. 3I the file ‘CBSUM’ is selected usingthe pop down menu). Fields 292 specify the variables 256 to be mapped toresult data 335. Field 293 indicates the permissible values (in thisexample, ‘Y’ or ‘N’) which the selected variable in the list 292 canhave. Fields 294 provide a quick means of locating a variable that hasalready been mapped using the pop-down menu to select the column of datato search such as Variable Name, or Result Field, then entering thecorresponding value to refine the search. The list 295 contains theattribute result and further describes the result type followed by thedata type and relative position of the data within the result file 335.The user can select from among these variables 256 shown in list 292 toadd to the list 295. Alternatively, by selecting a variable 256 in thelist 295 and selecting the remove control 296, a user can delete avariable 256 from the listing 295. Controls 297 enable a user to createa new output file mapping with a ‘New’ Control, to delete an existingoutput file mapping with ‘Delete’ control, or to edit an existing outputfile mapping with the ‘Edit’ control.

FIG. 3J is a view of a ‘User Defined Display Specification’ userinterface 2000 generated by the design module 200 of the computer 201.The user interface 2000 can be operated by a user to format of displayof variables 256 and data 307. Fields 2002 identify the client and sitename (the client is indicated as ‘0000’ and site is indicated as ‘280’in FIG. 3J), the view name (‘TST’ in FIG. 3J) for display 2004, and adescription of the screen contents or purpose (indicated as ‘CONSUMERSUMMARY SCREEN’ in FIG. 3J), and a field identifying the screen 2004being displayed (‘ViewID: TST’ in FIG. 3J). Using the cursor 243 theuser can configure the screen 2004. The user can move the cursor 243 toa selected location of the screen 2004 using a mouse, for example. Theuser can then use the keyboard of computer 201 in order to entercharacters to define static text to be displayed in the screen 2004. Forexample, in FIG. 3J the user can enter the static identifiers ‘CREDITREPORT DISPLAY’ to identify the display 2004 in a manner that can bereadily understood by the user, the static data ‘RPT DATE’ indicates thedate of the credit report, etc. The values for the fields are derived byusing the cursor 243 to select one of the variables from file listing2006 and ‘dragging’ and ‘dropping’ the variable to the correspondingfield of the screen display 2004. Because the field size and data type(for instance, numeric, alphabetic or alphanumeric) has been previouslydefined for the variable (see e.g. FIG. 3H), the design module 200automatically generates a field of appropriate size to incorporate intothe screen display 2004 at the position indicated by the user.Furthermore, the design module 200 indicates the field position in thedisplay 2004 in a color scheme identified by legend 2008 so that theuser can readily comprehend the type of data that is to be displayed inthe corresponding field upon generation of the display 2004 (forexample, ‘XXXXXXXXX’ displayed in a particular color can be used toindicate that the corresponding field has a value derived from a definedvariable). The list 2006 shown in FIG. 3J is that which results uponselecting the ‘Summary’ tab of the tabs 2008. Other tabs 2008 includethe ‘Page Header’ tab to define the layout of the page header, the ‘PageFooter’ tab to define the layout of the page footer, and the ‘Segment’tag to define the detailed data 307. The user also has the option ofselecting the ‘Remove’ button 2010 to delete a “tabs worth” ofspecifications. In addition, the user can operate the design module 200using cursor 243 to activate the controls 2012. The ‘New’ control 2012can be used to create a new screen 2004, the ‘Delete’ control 2012 canbe used to delete a screen 2004, the ‘Edit’ control can be used to editan existing screen 2004 and the ‘Copy’ control can be used to copy ascreen 2004, for example, as the basis for a new screen display to avoidduplication of effort in preparing the screen layout.

FIG. 3K is a view of a ‘Decision Assistant’ user interface 2020generated by the design module 200 of the computer 201. The userinterface 2020 is designed to enable the user to create decision rules210 used to generate result data files 335 from the data provider's data307. The decision rules 210 developed with the Decision Assistant aredefined in a language which is intuitive to the user. For example, underthe heading ‘MAIN BUSINESS EVALUATION CARD’ the following rule structureis provided:

MAIN BUSINESS EVALUATION CARD 001 Group 1 001 if CSV-BANKRUPTCY = Y thenSTATUS = Q, REASON = 10 x or

-   Thus, user interface 2020 provides that for Group 1 of a    hierarchical tree of logic defining decision rules 210, that if for    line 001 of the code the variable ‘CSV-BANKRUPTCY’ is ‘Y’ (meaning    ‘YES’) then the ‘STATUS’ variable is equal to code ‘Q’ and the    ‘REASON’ variable is equal to code ‘10x’. If not, then control    proceeds to the logic defined for Group 2 of the decision rules, and    so forth. A user thus has the ability to define the logic required    for the decision rules 210 without having to be a programmer skilled    in a particular computer language to do so.

FIG. 3L is a view of a ‘Decision Rule’ defining user interface 2030generated by the design module 200 of the computer 201. The userinterface 2030 is designed to enable the user to create the decisionrules 210, such as the lines of logic shown in FIG. 3K. The userinterface 2030 includes a source field 2031 which enables the user todefine the source file “Data File” for the first operand to which thedecision rules 210 being developed are to be applied. The source field2031 also has a ‘Data Field’ that enables the user to select thevariable name associated with the data for the first operand to whichthe user desires to apply the rule. The ‘Score’, ‘Status’, and ‘Reason’fields designate the output variables for the results of applying thedecision rules 210 to the data. The ‘Storage’ field enables the user todefine where in memory the result is to be stored. The operator field2032 allows the user to define the logical operator or function to beused to operate on the first and second operands defined in fields 2031and 2033, respectively. Using a pop-down menu, the user can selectvarious mathematical or logical operations such as ‘equal’, ‘less than’,‘greater than’, etc. In addition, the user has the option of selectingthe second operand from fields 2033. Using the fields 2033 and thecomputer's input/output devices, the user can enter a ‘value’ for thesecond operand, indicate whether that operand is numeric oralphanumeric, or leave the field blank (thus, assign a ‘0’ value to thesecond operand). In addition, the user can use field 2033 to indicatewhether the second operand is a ‘Score’, ‘Status’, or ‘Reason’ variable,and also a ‘Storage’ field to indicate where in memory the secondoperand is stored in order to locate it for comparison. The fields 2034can be used by the user to select the ‘Status’ and ‘Reason’ codes to beassociated with the result of the operation on the first and secondoperands. The field 2035 is used to define the relationship of thedecision rule 210 defined with window 2040 to the decision rulefollowing in the logical hierarchy (see, e.g., in FIG. 3K how the last‘or’ operation of line 001 of Group 1 logically links the Group 1 rulesto the Group 2 rules following). The ‘Group’ field 236 can be used todefine the Group of rules to which the decision rule is to be routed,and the ‘Rule Set’ field 2036 is used to specify the rule set to whichthe defined rule is routed if the rule evaluates to be true. The field2037 indicates the logical statement of the rule as it will appear in aline of the hierarchical tree of the decision rules 210. Field 2038 is acomment field enabling a user to type in a comment, e.g., a statement ofthe purpose of the rule as a guide to future editing and debugging).Finally, with respect to FIG. 3L, the controls 2039 enable the user tosave the rule 210 by activated the ‘Ok’ button, or to reject the ruleand exit window 2040 without saving the rule 210.

FIG. 3M is a user interface 2050 generated by the design module 200 ofthe computer 201. The design module 200 includes a listing of a codefile 2052. The listing 2052 is selected using the menu in field 2054,i.e., the particular listing is a ‘Reason’ code file. The listing 2052relates the codes 2056 (01, 02, 03, etc.) to corresponding reasons 2058(‘INSUFFICIENT LENGTH OF CREDIT HISTORY’, ‘***Code added duringimport***’, ‘RECENT DELINQUENCY’, etc.). The use of codes 2056 makes itpossible to reference textual reasons in a shorthand way. These codesare used to identify the specifics of decision made. For example, if anapplicant was denied credit, the reason, “INSUFFICIENT LENGTH OF CREDITHISTORY” could be communicated to the consumer.

FIG. 3N is an ‘Export’ user interface 2060 generated by the designmodule 200 of the computer 201. The user interface 2060 enables a userto select decision rule sets 210 for export to the execution engine 300to be applied against data 205 identified by the specification file 205.More specifically, the user operates the input device to move cursor 243to check boxes 2064 to select corresponding rules sets 210 for export tothe execution engine 300. Field 2065 enables the user to specify thelocation in memory (e.g., directory path and filename) for the filecontaining selected rule set(s) 210. The controls 2066 enable the userto select all or de-select all files for export. The control 2067enables a user to view a selected rule set 210. The ‘Start’ control 2068enables the user to transmit selected rule sets 210 to the export filelocation in memory for export to the execution engine 300. Export to theexecution engine 300 can be performed automatically upon operation ofthe ‘Start’ control 2068, or it may be performed with the involvement ofthe user, e.g., by emailing the files from the export file location tothe data provider 600 for import into the execution engine 300. Thecheck box 2069 enables the user to indicate whether the rule set changedsince the last export, making it necessary for at least the changedportions of the file to be exported to the execution engine 300.

FIG. 3O is a view of a ‘Prescreen Attribute Management’ user interface2090 which enables a user to evaluate the effectiveness of theattributes selected for use in a marketing campaign through results 335they generate when processed by the execution engine 300. User interface2090 is generated by the performance management module 400 executed bycomputer 401. The campaign name field 2091 identifies the marketingcampaign to which the attributes relate. The marketing campaign could bea solicitation for credit card applications, loan applications, etc. orother product or service to be offered. The period field 2092 identifiesthe time period or dates over which the campaign is conducted. Thebudget field 2093 indicates the budget for the marketing campaign(‘$5,900,000’). The type field indicates the type of marketing campaignto be conducted. In this case, the type field (‘acquire’) indicates thepurpose of the marketing campaign is to acquire applications for creditcards. The status field 2096 indicates whether the campaign is active,suspended, inactive, etc. The field 2095 indicates the personresponsible for the campaign. The region field 2096 indicates thegeographic region in which the campaign is being conducted. Theobjective field 2098 indicates the purpose of the marketing campaign. Inthis case, the object is to ‘acquire new card holders.’ The divisionfield 2099 indicates the division of the business that is conducting themarketing campaign.

Still referring to FIG. 3O the performance listing 3015 identifies thesource 3002 (i.e., the data provider 300 that provided the data [e.g.,Equifax, Experian, Trans Union, etc.]), the target count 3003 of creditcard applications sought in the campaign, the actual count 3004 ofcredit card applications received in the campaign, the status date 3005for which the data in the line item of the listing 3015 is relevant, theattribute set 3006 used in the marketing campaign to identify potentialapplicants to whom applications were sent in the campaign, the expectedresponse 3007 based on past experience with similar applications and/orpotential applicants, the expected response 3007 indicating the expectednumber of applicants to respond with credit card applications, theactual response 3008 indicating the actual number of applicantsresponding with credit card applications, and the percentage response3009 which is a percentage derived by dividing the number of actualapplicants by the number of solicitations sent to potential applicants,multiplied by one-hundred. The field 3010 indicates the monetary amountallocated by the business to the campaign, and field 3011 indicates theportion of the amount allocated that remains available to be spent. Thefield 3012 indicates the percentage return of applications averaged forsolicitations provided for all data providers. Finally, the notes field3013 indicates any comments the user desires to make regarding thecampaign.

Those of ordinary skill in the art will appreciate that the wealth ofinformation provided by the user interface 2090 provides the capabilityto effectively manage a marketing campaign using the performancemanagement module 400. It can be used to identify attribute sets thatare most likely to generate a desired pool of applicants or customersthat a business desires for a marketing campaign. This enables thebusiness to spend funds allocated for marketing campaigns in a mannermost beneficial for the business. In addition, by varying the attributesets used in marketing campaigns, the business can adjust marketingcampaigns (eg, the pool of prospective applicants to which solicitationsare sent, the criteria used for acceptance of applicants, etc.) toobtain the desired results from the campaign. In addition, through theuse of identifiers common to related sets of attribute files, decisionrule files, result data, and performance data, the user can gauge theperformance of attributes and decision rules in generating the customersthe client desires. In addition, because the FCRA and other laws requirethe attributes and decision rules to be applied consistently insolicitations and acceptance of applicants as customers, the presentinvention enables the user to comply with applicable law.

Although the invention described herein has been applied to specificembodiments related primarily to credit risk analysis, it should beunderstood that the subject invention can be applied to other fields.Such fields include use of restricted data to perform checks forprospective or current employees or others, including criminal,security, visa, immigration, driving record or financial status checks.Other fields to which the invention can be applied include use ofrestricted data to authenticate a person's identity, to detect andprevent fraud in financial transactions, to conduct security checks orclearances on employees, agents or others, to determine marketing creditor financial status or rating of a company or individual, to conductdemographic marketing, or to assess, analyze or underwrite medical orinsurance risks. Virtually any field in which access to data isregulated by law or federal agency can benefit from use of the subjectinvention, including the fields of consumer protection or nationalsecurity. In general, any field that requires processing of data towhich access is restricted by law, regulation, business practice,ethical considerations (for example, legal or medical confidences) orfor other reason that is used to generate a result provided outside ofthe zone of restriction in which the data resides (for example, anorganization hosting the restricted data) can benefit from the claimedinvention.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseinventions pertain having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the inventions are not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

All trademarks or service marks referenced herein are the property oftheir respective owners. Reference to the marks is for the purpose ofidentifying the source of particular products or services. In the caseof marks other than those of the assignee, reference to the marks is notintended in any way to trade upon the good will those owners haveestablished in those marks, or to make other than fair use thereof.

1. A system comprising: a first computer located at a client site, thefirst computer comprising one or more memory storage areas and one ormore processors, the one or more processors configured to: run a designmodule permitting a user to define a set of one or more attributes andone or more decision rules, wherein the set of one or more attributesand one or more decision rules are to be applied to a data provider'sdata comprising a plurality of data records corresponding respectivelyto a plurality of consumer data profiles; and transmit the set of one ormore attributes and one or more decision rules to a second computerlocated at the data provider's site; and the second computer comprisingone or more memory storage areas and one or more processors, the one ormore processors configured to: receive the set of one or more attributesand one or more decision rules; run an execution engine applying the setof one or more attributes and one or more decision rules to a portion ofthe data provider's data; identify a plurality of data recordscorresponding respectively to a plurality of consumer data profiles fromthe data provider's data satisfying the set of one or more attributesand one or more decision rules; generate result data based on theplurality of data records from the data provider's data satisfying theset of one or more attributes and one or more decision rules, whereinthe result data (a) comprises at least a portion of each data record ofthe plurality of data records from the data provider's data satisfyingthe set of one or more attributes and one or more decision rules, and(b) does not include credit data that would fall under Fair CreditReporting Act (FCRA) regulations; and transmit the result data to thefirst computer.
 2. A system as claimed in claim 1, wherein the one ormore processors of the first computer are further configured to: receivethe result data from the second computer.
 3. A system as claimed inclaim 1, wherein the one or more processors of the first computer arefurther configured to transmit the set of one or more attributes and oneor more decision rules on a single transaction basis in response to aninquiry.
 4. A system as claimed in claim 1, wherein the execution enginecarries out a batch of transactions to produce the result data.
 5. Asystem as claimed in claim 1, wherein the one or more processors of thefirst computer are further configured to: receive the result data fromthe second computer, wherein the set of one or more attributes and oneor more decision rules is used by an entity to obtain contactinformation of consumers from the data provider to send a solicitationthat includes an application for a benefit or offering of a marketingcampaign associated with an entity; receive performance data, whereinthe performance data indicates: a number of applications returned byconsumers, a number of applications accepted by the entity for thebenefit or offering, a payment performance of the consumers under thebenefit or offering, and a profitability of the benefit or offering, andcause to display information indicating the performance of the marketingcampaign based on the performance data.
 6. A system as claimed in claim5, wherein the one or more processors of the first computer are furtherconfigured to receive the result data automatically from the secondcomputer.
 7. A system as claimed in claim 5, wherein the benefit oroffering is for use of a credit card.
 8. A system as claimed in claim 5,wherein the benefit or offering is for a loan for the purchase of atleast one of real estate, a vehicle, an aircraft, a watercraft, anelectronic consumer device, or a consumer appliance.
 9. A system asclaimed in claim 5, wherein the result data includes a recommendation ora decision as to consumers to whom applications are to be sent by theentity for the marketing campaign.
 10. A system as claimed in claim 5,wherein: the one or more processors of the second computer are furtherconfigured to: associate a unique identifier with the result data andthe set of one or more attributes and one or more decision rules thatgenerated the result data, and the one or more processors of the firstcomputer are further configured to: assign the unique identifier to theperformance data indicating the number of applications returned, thenumber of applications accepted by the entity for the benefit oroffering, the payment performance of the consumers under the benefit oroffering, and the profitability of the benefit or offering, so thatperformance of the marketing campaign can be tracked in relation to theattributes and decision rules used to generate the consumers to whom theentity extends the benefit or offer.